Along with the widespread utilization of computer technology, the practice of saving information in electronic documents is gradually taking the place of conventional information storage method. The methods for querying in electronic documents at present mainly include text query based on character matching. However, in practice, a great amount of useless texts besides wanted texts would be presented by using conventional methods for query since the inputted query conditions are usually not precise enough. Users generally need to manually filter the query results, which means the query results are not precise. In addition, the information saved in electronic documents includes not only texts, but also varieties of graphics, images, even media information; while the conventional methods for query are able to handle texts only. Though a few methods for query of graphics and images are available now, those methods for query are only capable of detecting the presence of images and locating the images, and cannot be used for query of specific targets based on the query conditions given by the user.
It can be seen that conventional methods for character-based electronic document query are unable to satisfy the demands for full-scale, highly efficient and accurate queries.